library(dplyr)
library(tidyverse)
library(knitr)
library(plotly)
library(kableExtra)

1 Introduction

2 Domain knowledge

3 Country scale

3.1 Data sources

3.1.1 World bank data

3.1.1.1 Data provider

3.1.1.2 Data exploration

  • Total greenhouse gas emissions (kt of CO2 equivalent)
library(WDI)
 
#get datasets on emissions
datasets = WDIsearch("emissions")

# get Total greenhouse gas emissions (kt of CO2 equivalent)

ghg_emissions_wb = WDI(indicator='EN.ATM.GHGT.KT.CE')

# get all world data
ghg_emissions_wb_world = ghg_emissions_wb %>% 
  filter(country == "World")

# Show data sample 
ghg_emissions_wb_world %>% 
  top_n(10) %>% 
  kable() %>%
  kable_styling(bootstrap_options = c("striped", "hover"), full_width = F, font_size = 13) %>% 
  scroll_box(width = "100%", height = "400px")
iso2c country EN.ATM.GHGT.KT.CE year
1W World NA 2020
1W World NA 2019
1W World NA 2018
1W World NA 2017
1W World NA 2016
1W World NA 2015
1W World NA 2014
1W World NA 2013
1W World 53526303 2012
1W World 52790527 2011 
# plot world GHG emissions
ghg_emissions_wb_world %>% 
  plot_ly() %>% 
  add_trace(y = ~EN.ATM.GHGT.KT.CE, 
            x = ~year, 
            marker = list(color = "gray"),
            type = 'scatter',
            # type = "line",
            mode = 'lines+markers',
            orientation = "v") %>% 
  layout(title = "World GHG emissions (source: WorldBank)",
         yaxis = list(title = "GHG emissions"), 
         xaxis = list(title = "Years"))

3.1.2 World Resources Institute

3.1.2.1 Data provider

3.1.2.2 Data exploration

  • Data is provided by API or download
  • In this example we will explore the dwonloaded data
# load data
ghg_emissions_wri = read.csv("https://raw.githubusercontent.com/OpenGeoScales/CarbonData/feature-article/datasets/raw/wri/historical_emissions/historical_emissions.csv", 
                             encoding = "UTF-8")
  • Data contains GHG emissions timeserie in wide format
Column Description
Country The country name
Data.source Five data sources: CAIT, PIK, GCP, UNFCCC_AI, UNFCCC_NAI
Sector 30 categories of sectors: Total including LUCF,Total excluding LUCF, Total fossil fuels and cement, Electricity/Heat, Coal, Oil…
Gas 8 categories of sectors: All GHG,KYOTOGHG, CO2, Aggregate GHGs, CH4, N2O, F-Gas , Aggregate F-gases
Unit One unit: MtCO₂e
1850 Emission quantity in 1850
1851 Emission quantity in 1850
.. Emission quantity in 1851
2019 Emission quantity in 2019
  • Sector categories by data source : Categories used for sectors and gases depend on data source.
# get sectors from different data sources
sector_CAIT = ghg_emissions_wri %>% 
  filter(Data.source == "CAIT") %>% 
  distinct(Sector) %>% 
  select(Sector.CAIT = Sector) %>% 
  arrange(Sector.CAIT)

sector_PIK = ghg_emissions_wri %>% 
  # select PIK datasource
  filter(Data.source == "PIK") %>% 
  distinct(Sector) %>% 
  select(Sector.PIK = Sector) %>% 
  arrange(Sector.PIK)

sector_GCP = ghg_emissions_wri %>% 
  # select GCP datasource
  filter(Data.source == "GCP") %>% 
  distinct(Sector) %>% 
  select(Sector.GCP = Sector) %>% 
  arrange(Sector.GCP)

sector_UNFCCC_AI = ghg_emissions_wri %>% 
  # select UNFCCC_AI datasource
  filter(Data.source == "UNFCCC_AI") %>% 
  distinct(Sector) %>%  
  select(Sector.UNFCCC_AI = Sector) %>% 
  arrange(Sector.UNFCCC_AI)

sector_UNFCCC_NAI = ghg_emissions_wri %>% 
  # select UNFCCC_NAI datasource
  filter(Data.source == "UNFCCC_NAI") %>% 
  distinct(Sector) %>% 
  select(Sector.UNFCCC_NAI = Sector) %>% 
  arrange(Sector.UNFCCC_NAI)

# plot table
knitr::kable(list(sector_CAIT, sector_PIK, sector_GCP, sector_UNFCCC_AI, sector_UNFCCC_NAI)) %>% 
  kable_styling(bootstrap_options = c("striped", "hover"), full_width = F, font_size = 12) %>% 
  scroll_box(width = "100%", height = "200px")
Sector.CAIT
Agriculture
Building
Bunker Fuels
Electricity/Heat
Energy
Fugitive Emissions
Industrial Processes
Land-Use Change and Forestry
Manufacturing/Construction
Other Fuel Combustion
Total excluding LUCF
Total including LUCF
Transportation
Waste
Sector.PIK
Agriculture
Energy
Industrial Processes and Product Use
Other
Total excluding LULUCF
Waste
Sector.GCP
Bunkers
Cement
Coal
Gas
Gas flaring
Oil
Total fossil fuels and cement
Sector.UNFCCC_AI
Agriculture
Energy
Industrial Processes and Product Use
Land Use, Land-Use Change and Forestry
Other
Total GHG emissions with LULUCF
Total GHG emissions without LULUCF
Waste
Sector.UNFCCC_NAI
Agriculture
Energy
Industrial Processes
Land-Use Change and Forestry
Other
Solvent and Other Product Use
Total GHG emissions excluding LULUCF/LUCF
Total GHG emissions including LULUCF/LUCF
Waste
  • Gas categories by data source : Categories used for gases depend on data source.
# get gas from different data sources
gas_CAIT = ghg_emissions_wri %>% 
  filter(Data.source == "CAIT") %>% 
  distinct(Gas) %>% 
  select(Gas.CAIT = Gas) %>% 
  arrange(Gas.CAIT)

gas_PIK = ghg_emissions_wri %>% 
  # select PIK datasource
  filter(Data.source == "PIK") %>% 
  distinct(Gas) %>% 
  select(Gas.PIK = Gas) %>% 
  arrange(Gas.PIK)

gas_GCP = ghg_emissions_wri %>% 
  # select GCP datasource
  filter(Data.source == "GCP") %>% 
  distinct(Gas) %>% 
  select(Gas.GCP = Gas) %>% 
  arrange(Gas.GCP)

gas_UNFCCC_AI = ghg_emissions_wri %>% 
  # select UNFCCC_AI datasource
  filter(Data.source == "UNFCCC_AI") %>% 
  distinct(Gas) %>%  
  select(Gas.UNFCCC_AI = Gas) %>% 
  arrange(Gas.UNFCCC_AI)

gas_UNFCCC_NAI = ghg_emissions_wri %>% 
  # select UNFCCC_NAI datasource
  filter(Data.source == "UNFCCC_NAI") %>% 
  distinct(Gas) %>% 
  select(Gas.UNFCCC_NAI = Gas) %>% 
  arrange(Gas.UNFCCC_NAI)

# plot table
knitr::kable(list(gas_CAIT, gas_PIK, gas_GCP, gas_UNFCCC_AI, gas_UNFCCC_NAI)) %>% 
  kable_styling(bootstrap_options = c("striped", "hover"), full_width = F, font_size = 12) %>% 
  scroll_box(width = "100%", height = "200px")
Gas.CAIT
All GHG
CH4
CO2
F-Gas
N2O
Gas.PIK
CH4
CO2
F-Gas
KYOTOGHG
N2O
Gas.GCP
CO2
Gas.UNFCCC_AI
Aggregate F-gases
Aggregate GHGs
CH4
CO2
N2O
Gas.UNFCCC_NAI
Aggregate F-gases
Aggregate GHGs
CH4
CO2
N2O
3.1.2.2.1 CAIT data source

In this example we will only on CAIT data source

# data processing

ghg_emissions_wri_CAIT = ghg_emissions_wri %>% 
  # select all world data & all gases data & total sector
  filter(Data.source == "CAIT",
         Country == "World", 
         Gas == "All GHG",
         Sector == "Total including LUCF") %>% 
  # pivot data
  pivot_longer(
    cols = starts_with("X"), 
    names_to = "year",
    names_prefix = "X",
    values_to = "value") %>% 
  mutate_at("year" , as.numeric) %>% 
  arrange(year)

# plot table
ghg_emissions_wri_CAIT %>% 
  kable() %>%
  kable_styling(bootstrap_options = c("striped", "hover"), full_width = F, font_size = 13) %>% 
  scroll_box(width = "100%", height = "200px")
Country Data.source Sector Gas Unit year value
World CAIT Total including LUCF All GHG MtCO2e 1850 N/A
World CAIT Total including LUCF All GHG MtCO2e 1851 N/A
World CAIT Total including LUCF All GHG MtCO2e 1852 N/A
World CAIT Total including LUCF All GHG MtCO2e 1853 N/A
World CAIT Total including LUCF All GHG MtCO2e 1854 N/A
World CAIT Total including LUCF All GHG MtCO2e 1855 N/A
World CAIT Total including LUCF All GHG MtCO2e 1856 N/A
World CAIT Total including LUCF All GHG MtCO2e 1857 N/A
World CAIT Total including LUCF All GHG MtCO2e 1858 N/A
World CAIT Total including LUCF All GHG MtCO2e 1859 N/A
World CAIT Total including LUCF All GHG MtCO2e 1860 N/A
World CAIT Total including LUCF All GHG MtCO2e 1861 N/A
World CAIT Total including LUCF All GHG MtCO2e 1862 N/A
World CAIT Total including LUCF All GHG MtCO2e 1863 N/A
World CAIT Total including LUCF All GHG MtCO2e 1864 N/A
World CAIT Total including LUCF All GHG MtCO2e 1865 N/A
World CAIT Total including LUCF All GHG MtCO2e 1866 N/A
World CAIT Total including LUCF All GHG MtCO2e 1867 N/A
World CAIT Total including LUCF All GHG MtCO2e 1868 N/A
World CAIT Total including LUCF All GHG MtCO2e 1869 N/A
World CAIT Total including LUCF All GHG MtCO2e 1870 N/A
World CAIT Total including LUCF All GHG MtCO2e 1871 N/A
World CAIT Total including LUCF All GHG MtCO2e 1872 N/A
World CAIT Total including LUCF All GHG MtCO2e 1873 N/A
World CAIT Total including LUCF All GHG MtCO2e 1874 N/A
World CAIT Total including LUCF All GHG MtCO2e 1875 N/A
World CAIT Total including LUCF All GHG MtCO2e 1876 N/A
World CAIT Total including LUCF All GHG MtCO2e 1877 N/A
World CAIT Total including LUCF All GHG MtCO2e 1878 N/A
World CAIT Total including LUCF All GHG MtCO2e 1879 N/A
World CAIT Total including LUCF All GHG MtCO2e 1880 N/A
World CAIT Total including LUCF All GHG MtCO2e 1881 N/A
World CAIT Total including LUCF All GHG MtCO2e 1882 N/A
World CAIT Total including LUCF All GHG MtCO2e 1883 N/A
World CAIT Total including LUCF All GHG MtCO2e 1884 N/A
World CAIT Total including LUCF All GHG MtCO2e 1885 N/A
World CAIT Total including LUCF All GHG MtCO2e 1886 N/A
World CAIT Total including LUCF All GHG MtCO2e 1887 N/A
World CAIT Total including LUCF All GHG MtCO2e 1888 N/A
World CAIT Total including LUCF All GHG MtCO2e 1889 N/A
World CAIT Total including LUCF All GHG MtCO2e 1890 N/A
World CAIT Total including LUCF All GHG MtCO2e 1891 N/A
World CAIT Total including LUCF All GHG MtCO2e 1892 N/A
World CAIT Total including LUCF All GHG MtCO2e 1893 N/A
World CAIT Total including LUCF All GHG MtCO2e 1894 N/A
World CAIT Total including LUCF All GHG MtCO2e 1895 N/A
World CAIT Total including LUCF All GHG MtCO2e 1896 N/A
World CAIT Total including LUCF All GHG MtCO2e 1897 N/A
World CAIT Total including LUCF All GHG MtCO2e 1898 N/A
World CAIT Total including LUCF All GHG MtCO2e 1899 N/A
World CAIT Total including LUCF All GHG MtCO2e 1900 N/A
World CAIT Total including LUCF All GHG MtCO2e 1901 N/A
World CAIT Total including LUCF All GHG MtCO2e 1902 N/A
World CAIT Total including LUCF All GHG MtCO2e 1903 N/A
World CAIT Total including LUCF All GHG MtCO2e 1904 N/A
World CAIT Total including LUCF All GHG MtCO2e 1905 N/A
World CAIT Total including LUCF All GHG MtCO2e 1906 N/A
World CAIT Total including LUCF All GHG MtCO2e 1907 N/A
World CAIT Total including LUCF All GHG MtCO2e 1908 N/A
World CAIT Total including LUCF All GHG MtCO2e 1909 N/A
World CAIT Total including LUCF All GHG MtCO2e 1910 N/A
World CAIT Total including LUCF All GHG MtCO2e 1911 N/A
World CAIT Total including LUCF All GHG MtCO2e 1912 N/A
World CAIT Total including LUCF All GHG MtCO2e 1913 N/A
World CAIT Total including LUCF All GHG MtCO2e 1914 N/A
World CAIT Total including LUCF All GHG MtCO2e 1915 N/A
World CAIT Total including LUCF All GHG MtCO2e 1916 N/A
World CAIT Total including LUCF All GHG MtCO2e 1917 N/A
World CAIT Total including LUCF All GHG MtCO2e 1918 N/A
World CAIT Total including LUCF All GHG MtCO2e 1919 N/A
World CAIT Total including LUCF All GHG MtCO2e 1920 N/A
World CAIT Total including LUCF All GHG MtCO2e 1921 N/A
World CAIT Total including LUCF All GHG MtCO2e 1922 N/A
World CAIT Total including LUCF All GHG MtCO2e 1923 N/A
World CAIT Total including LUCF All GHG MtCO2e 1924 N/A
World CAIT Total including LUCF All GHG MtCO2e 1925 N/A
World CAIT Total including LUCF All GHG MtCO2e 1926 N/A
World CAIT Total including LUCF All GHG MtCO2e 1927 N/A
World CAIT Total including LUCF All GHG MtCO2e 1928 N/A
World CAIT Total including LUCF All GHG MtCO2e 1929 N/A
World CAIT Total including LUCF All GHG MtCO2e 1930 N/A
World CAIT Total including LUCF All GHG MtCO2e 1931 N/A
World CAIT Total including LUCF All GHG MtCO2e 1932 N/A
World CAIT Total including LUCF All GHG MtCO2e 1933 N/A
World CAIT Total including LUCF All GHG MtCO2e 1934 N/A
World CAIT Total including LUCF All GHG MtCO2e 1935 N/A
World CAIT Total including LUCF All GHG MtCO2e 1936 N/A
World CAIT Total including LUCF All GHG MtCO2e 1937 N/A
World CAIT Total including LUCF All GHG MtCO2e 1938 N/A
World CAIT Total including LUCF All GHG MtCO2e 1939 N/A
World CAIT Total including LUCF All GHG MtCO2e 1940 N/A
World CAIT Total including LUCF All GHG MtCO2e 1941 N/A
World CAIT Total including LUCF All GHG MtCO2e 1942 N/A
World CAIT Total including LUCF All GHG MtCO2e 1943 N/A
World CAIT Total including LUCF All GHG MtCO2e 1944 N/A
World CAIT Total including LUCF All GHG MtCO2e 1945 N/A
World CAIT Total including LUCF All GHG MtCO2e 1946 N/A
World CAIT Total including LUCF All GHG MtCO2e 1947 N/A
World CAIT Total including LUCF All GHG MtCO2e 1948 N/A
World CAIT Total including LUCF All GHG MtCO2e 1949 N/A
World CAIT Total including LUCF All GHG MtCO2e 1950 N/A
World CAIT Total including LUCF All GHG MtCO2e 1951 N/A
World CAIT Total including LUCF All GHG MtCO2e 1952 N/A
World CAIT Total including LUCF All GHG MtCO2e 1953 N/A
World CAIT Total including LUCF All GHG MtCO2e 1954 N/A
World CAIT Total including LUCF All GHG MtCO2e 1955 N/A
World CAIT Total including LUCF All GHG MtCO2e 1956 N/A
World CAIT Total including LUCF All GHG MtCO2e 1957 N/A
World CAIT Total including LUCF All GHG MtCO2e 1958 N/A
World CAIT Total including LUCF All GHG MtCO2e 1959 N/A
World CAIT Total including LUCF All GHG MtCO2e 1960 N/A
World CAIT Total including LUCF All GHG MtCO2e 1961 N/A
World CAIT Total including LUCF All GHG MtCO2e 1962 N/A
World CAIT Total including LUCF All GHG MtCO2e 1963 N/A
World CAIT Total including LUCF All GHG MtCO2e 1964 N/A
World CAIT Total including LUCF All GHG MtCO2e 1965 N/A
World CAIT Total including LUCF All GHG MtCO2e 1966 N/A
World CAIT Total including LUCF All GHG MtCO2e 1967 N/A
World CAIT Total including LUCF All GHG MtCO2e 1968 N/A
World CAIT Total including LUCF All GHG MtCO2e 1969 N/A
World CAIT Total including LUCF All GHG MtCO2e 1970 N/A
World CAIT Total including LUCF All GHG MtCO2e 1971 N/A
World CAIT Total including LUCF All GHG MtCO2e 1972 N/A
World CAIT Total including LUCF All GHG MtCO2e 1973 N/A
World CAIT Total including LUCF All GHG MtCO2e 1974 N/A
World CAIT Total including LUCF All GHG MtCO2e 1975 N/A
World CAIT Total including LUCF All GHG MtCO2e 1976 N/A
World CAIT Total including LUCF All GHG MtCO2e 1977 N/A
World CAIT Total including LUCF All GHG MtCO2e 1978 N/A
World CAIT Total including LUCF All GHG MtCO2e 1979 N/A
World CAIT Total including LUCF All GHG MtCO2e 1980 N/A
World CAIT Total including LUCF All GHG MtCO2e 1981 N/A
World CAIT Total including LUCF All GHG MtCO2e 1982 N/A
World CAIT Total including LUCF All GHG MtCO2e 1983 N/A
World CAIT Total including LUCF All GHG MtCO2e 1984 N/A
World CAIT Total including LUCF All GHG MtCO2e 1985 N/A
World CAIT Total including LUCF All GHG MtCO2e 1986 N/A
World CAIT Total including LUCF All GHG MtCO2e 1987 N/A
World CAIT Total including LUCF All GHG MtCO2e 1988 N/A
World CAIT Total including LUCF All GHG MtCO2e 1989 N/A
World CAIT Total including LUCF All GHG MtCO2e 1990 34964.58
World CAIT Total including LUCF All GHG MtCO2e 1991 35125.92
World CAIT Total including LUCF All GHG MtCO2e 1992 34982.15
World CAIT Total including LUCF All GHG MtCO2e 1993 35080.3
World CAIT Total including LUCF All GHG MtCO2e 1994 35283.88
World CAIT Total including LUCF All GHG MtCO2e 1995 36004.23
World CAIT Total including LUCF All GHG MtCO2e 1996 36022.1
World CAIT Total including LUCF All GHG MtCO2e 1997 37338.36
World CAIT Total including LUCF All GHG MtCO2e 1998 36981.63
World CAIT Total including LUCF All GHG MtCO2e 1999 36817.13
World CAIT Total including LUCF All GHG MtCO2e 2000 37438.04
World CAIT Total including LUCF All GHG MtCO2e 2001 38396.69
World CAIT Total including LUCF All GHG MtCO2e 2002 39855.92
World CAIT Total including LUCF All GHG MtCO2e 2003 40703.74
World CAIT Total including LUCF All GHG MtCO2e 2004 42477.66
World CAIT Total including LUCF All GHG MtCO2e 2005 43360.31
World CAIT Total including LUCF All GHG MtCO2e 2006 43739.49
World CAIT Total including LUCF All GHG MtCO2e 2007 44590.03
World CAIT Total including LUCF All GHG MtCO2e 2008 44953.73
World CAIT Total including LUCF All GHG MtCO2e 2009 44907.04
World CAIT Total including LUCF All GHG MtCO2e 2010 46637.83
World CAIT Total including LUCF All GHG MtCO2e 2011 47915.71
World CAIT Total including LUCF All GHG MtCO2e 2012 48477.53
World CAIT Total including LUCF All GHG MtCO2e 2013 49037.46
World CAIT Total including LUCF All GHG MtCO2e 2014 49494.56
World CAIT Total including LUCF All GHG MtCO2e 2015 49828.88
World CAIT Total including LUCF All GHG MtCO2e 2016 49312.19
World CAIT Total including LUCF All GHG MtCO2e 2017 49947.42
World CAIT Total including LUCF All GHG MtCO2e 2018 N/A
World CAIT Total including LUCF All GHG MtCO2e 2019 N/A

We observe that we don’t have values for years before 1990 neither after 2017. Let’s plot the timeserie:

ghg_emissions_wri_CAIT %>% 
  filter(year >= 1990 & year < 2017) %>% 
  plot_ly() %>% 
  add_trace(y = ~value, 
            x = ~year, 
            marker = list(color = "gray"),
            type = 'scatter',
            # type = "line",
            mode = 'lines+markers',
            orientation = "v") %>% 
  layout(title = "World GHG emissions (source: WRI - CAIT)",
         yaxis = list(title = "GHG emissions"), 
         xaxis = list(title = "Years"))

3.2 Data normalization

3.2.1 data modeling

  • We propose a data model for mapping the various data source identified
Column name Type Description
data.source string
data.provider string
geo.scale string
geo.code.iso2c string
geo.code.iso3c string
geo.name string
year numeric
sector string
gas string
value numeric
unit string 
# create dataset
OGS_ghg_emission = data.frame(data.source = as.character(),
                              data.provider = as.character(),
                              geo.scale = as.character(),
                              geo.code.iso2c = as.character(),
                              geo.code.iso3c = as.character(),
                              geo.name = as.character(),
                              year = as.numeric(),
                              sector = as.character(),
                              gas = as.character(),
                              value = as.numeric(),
                              unit = as.character())

3.2.2 Data mapping

  • Mapping WB data
OGS.MAP.WB = function(Worldbank_data, start_date, end_date){
  Worldbank_data_OGS = Worldbank_data %>% 
    add_column(data.source = "World.Bank",
               data.provider = "World.Bank",
               geo.scale = "Country",
               sector = "All",
               gas = "All",
               geo.code.iso3c = NA,
               unit = "MtCO₂e") %>% 
    rename(geo.code.iso2c = iso2c,
           geo.name = country,
           value = EN.ATM.GHGT.KT.CE) %>% 
    select(data.source, data.provider, geo.scale, geo.code.iso2c, geo.code.iso3c, geo.name,
           year, sector, gas, value) %>% 
    filter(year >= start_date & year <= end_date) %>% 
    mutate(value = value * 0.001)
  
  return(Worldbank_data_OGS)
}

Worldbank_data_OGS = OGS.MAP.WB(ghg_emissions_wb_world,
                                start_date = 1970,
                                end_date = 2012 )
  • Mapping WRI-CAIT data
OGS.MAP.WRI.CAIT = function(wri_data, start_date, end_date){
  wri_data_OGS = wri_data %>% 
    add_column(data.provider = "WRI.CAIT",
               geo.scale = "Country",
               sector = "All",
               geo.code.iso3c = NA,
               geo.code.iso2c = NA,
               unit = "MtCO₂e") %>% 
    rename(data.source = Data.source,
           geo.name = Country,
           gas = Gas,
           value = value) %>% 
    select(data.source, data.provider, geo.scale, geo.code.iso2c, geo.code.iso3c, geo.name,
           year, sector, gas, value) %>% 
    filter(year >= start_date & year <= end_date) %>% 
    mutate_at("value" , as.numeric) 
  
  return(wri_data_OGS)
}

wri_data_OGS = OGS.MAP.WRI.CAIT(ghg_emissions_wri_CAIT,
                                start_date = 1990,
                                end_date = 2016 )

3.2.3 Normalized data exploration

OGS_ghg_emission = bind_rows(Worldbank_data_OGS, 
                             wri_data_OGS)

# plot timeserie
OGS_ghg_emission %>% 
  plot_ly() %>% 
  add_trace(y = ~value, 
            x = ~year, 
            color = ~data.provider,
            type = 'scatter',
            # type = "line",
            mode = 'lines+markers',
            orientation = "v",
            hoverinfo = 'text',
            text = ~paste('</br> Year: ', year,
                          '</br> Value: ', value,
                          '</br> Gas: ', gas,
                          '</br> Sector: ', sector,
                          '</br> Source: ', data.provider)) %>% 
  layout(title = "World GHG emissions",
         yaxis = list(title = "GHG emissions (MtCO₂)"), 
         xaxis = list(title = "Years"))

4 City scale